implementing a successful data governance program · the data steward will work with subject matter...

#AnalyticsXC o p y r ig ht © 201 6, SAS In st i tute In c. A l l r ig hts r ese rve d.

Implementing a Successful Data Governance Program

Mary Anne HopperData Management Consulting ManagerSAS

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C o p y r ig ht © 201 6, SAS In st i tute In c. A l l r ig hts r ese rve d.

SAS Data Management Framework

SOLUTIONSMETHODS

DATA MANAGEMENTDATA GOVERNANCE

BUSINESS DRIVERS

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Decision MakingCustomer FocusCompliance

Mandates

Mergers &

AcquisitionsAt-Risk Projects

Operational

Efficiencies

BUSINESS DRIVERS

Big Data Management

Data Visualization

Data QualityData

Virtualization

Data ProfilingMetadata

ManagementData

ExplorationData

Monitoring

SOLUTIONS

Data Lifecycle

Reference and Master Data

Data Security

Data Architecture

Metadata Data QualityData

Administration

Data Warehousing & BI/Analytics

DATA MANAGEMENT

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Ro

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& T

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Decision-making Bodies

Guiding Principles

Program Objectives

Decision Rights

DATA GOVERNANCE

People

Process

Technology

METHODS

Business Data Glossary

Data LineageMaster/

Reference DM

Data Integration

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The Data Governance JourneyPlan the Program Design the Program Launch the Program

Phased approach to identify business needs, address opportunities, and plan efforts

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The Data Governance JourneyPlan the Program Design the Program Launch the Program

Define the objectives of the program and set a framework for how and when decisions will be made

• Initial Scope

• Objectives

• Guiding Principles

• Decision-making Bodies

• Decision Rights

• Roles and Responsibilities

• Program Charter

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Prioritize the Challenges!

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Business Value and Achievability

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Prioritize the Challenges!

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Defining DG Objectives

• What do we want to achieve with Data Governance?

• Can we measure against the objective?

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Objectives - Samples

• Maintain a correct and consistent definition of the data and its business rules

• Increase the consistency, availability, usability, and quality of internal and external data

• Eliminate redundant or conflicting business processes and practices

• Provide a robust framework that enables sustainable execution across multiple data domains

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Defining DG Guiding Principles

• Guiding principles are the set of common philosophies intended to direct a program or organization irrespective of day-to-day changes

• Ideally they will reflect the organization’s values and goals

• Their purpose is to serve as a philosophical touchstone for questions or dilemmas during Data Governance deployment

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Guiding Principles - Samples

• The customer will be ‘top of mind’

• Customer data attributes will be shared through a common process or interface

• Outcomes should enable a seamless, consistent experience for customers

• Systems of record will be held accountable for data quality

• Participation is mandatory

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Organizational Structure - SampleEnterprise Data Governance Steering Committee

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Business Processes, Application & Systems, Organization

Common Operating Framework & Processes

Data Management

Product/Item DG Council

DS Team

Product /Item

CustomerDG Council

DS Team

Customer

FinanceDG Council

DS Team

Finance

TBD DG Council

DS Team

TBD…

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Organizational Structure - SampleDG

Steering Committee

DGOffice

Data Steward Data Steward Data Steward

Data Management

DGSub-Committee

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The Data Governance Journey

Determine how decision making bodies will operate and how compliance and progress will be measured

• Key Activities and Decisions

• Assign Decision Making

• Identify Key Participants

• Operating Procedures

• Key Workflows

• Communication and Training

• Metrics

Plan the Program Design the Program Launch the Program

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DG Decision Making

RACI LegendR = Responsible (Do the Work)A = Accountable (Ensure the Work is Done/Approver)C = Consulted (Provide Input)I = Informed (Notified, Not Active Participant)

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Identifying the DG Actors

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DG Operating Procedures - Sample

Define DG Operating Procedures – what the actors need to know to become operational

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DG Workflow - Sample

Define key DG workflows –where the actors fit into the most important activities

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Program Measurement - Sample

Program measurement –measure and monitor against established objectives

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Roadmap - Sample

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The Data Governance Journey

Begin execution of roadmap; start small and expand

• DG Onboarding

• Execute Operating Model

• Policy Development

• Benefit Measurement

Plan the Program Design the Program Launch the Program

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What is a Policy?Policy

Formal set of statements that define how the data resources will be used or managed

Procedure Detailed instructions about how a policy is to be implemented

Standard Required configuration that is considered best practice

Best PracticeTechnique, method, process, or activity that is more effective at delivering a particular outcome than any other technique, method, process, etc

Data ManagementTactical execution and enforcement of data governance policies and standards

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• ‘Retailer’ will utilize a standard product-focused hierarchy to be called the ‘Enterprise Product Hierarchy’. Other user classifications or views may be used for specific business needs. Hierarchy structures will be sourced from a common location.

• The Data Governance Office, in partnership with the appropriate business entities and support from IT, will proactively assess, monitor, report, and improve data quality. For the purposes of this policy, data quality is defined as the conformance of data to the business definitions and the business rules (business metadata).

Policies can be broad or granular in nature – depends on the organization

Development process is still the same!

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Policy - SamplePolicy Component Sample Statement(s)

Policy Objective Identify the business needs and the associated business usage of product hierarchies and categories

- Define Retailer’s supported hierarchies and categories

- Identify usage

- Document process to maintain and manage changes

Provide foundation for detailed attribute definition and standardization

- Core Attributes

- Product Specific Selling Attributes

Provide the process to measure compliance

Policy ‘Retailer’ will utilize a standard product-focused hierarchy to be called the ‘Enterprise Product Hierarchy’. Other user

classifications or views may be used for specific business needs. Hierarchy structures will be sourced from a common

location

Procedure(s) All products will align to a standard product segment at product set-up in support of the Product Hierarchy.

All products will align to one or more business focus areas.

Product segment and business focus will determine data collection requirements, data management, process flow,

decision rights, and data ownership.

Standard(s) Segment Family Class Brick GTIN

Compliance Product on-boarding aligned to standard hierarchy

Legacy systems updated to align to product-focused hierarchy

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Policy - SamplePolicy Component Sample Statement(s)

Policy Objective Understand and define data quality baseline.

Define data quality measures.

Ensure data quality issues are corrected at their source.

Compliance Compliance is achieved for high-impact data elements when:

Data is profiled

Measures defined

SLA defined

Ongoing quality monitored

Policy The Data Governance Office, in partnership with the appropriate business entities and support from IT, will proactively

assess, monitor, report, and improve data quality. For the purposes of this policy, data quality is defined as the

conformance of data to the business definitions and the business rules (business metadata).

Procedure(s) The Data Stewards will evaluate the quality of the data in a specific focus area.

The Data Steward will work with subject matter experts within the business to establish data quality measures and

remediation steps for high impact data elements.

The DG Office will work with data producers and data consumers to establish Data Quality SLAs

Standard(s) The DQ process will follow the defined closed loop process.

The common set of DQ tools will be utilized for DQ activities.


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implementing a successful data governance program · the data steward will work with subject matter...

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